(1) Field of the Invention
The present invention relates generally to information storage and retrieval, and more particularly to knowledge-based information storage and retrieval.
(2) Description of the Prior Art
A computer does not store, process, or retrieve information in the same manner as the human brain. In nearly all instances, the human knowledge processing system is more efficient than existing computer processing algorithms. Research and concepts including neural networks, fuzzy logic, etc., attempt to simulate the human brain""s vast capability to learn and associate in complex manners. U.S. Pat. No. 5,761,496 to Hattori presents an information retrieval system that retrieves information on a trial and error basis based upon a keyword input by the user and previously stored background information. Alternately, U.S. Pat. No. 6,026,393 to Gupta et al. presents a system and method to reduce the cases applicable to a current problem in a case-based reasoning system. U.S. Pat. No. 6,038,560 to Wical discloses a concept knowledge base search and retrieval system wherein document theme vectors allow a query system to produce terminology that identifies the potential existence of documents for the queried subject matter. Such existing systems are useful for retrieving a particular class or category of data, where the data is of one particular species. These systems implement rule-based solutions as opposed to structure-based solutions that are constructed in the human brain. This is a severe limitation for continued progress in robotics and artificial intelligence.
The human brain""s associative capabilities are not limited like a computer to words or pure binary data stimuli. The human brain makes associations based upon visual data, auditory data, sensory data such as touch, and motion data, all of which emanate from the physical world. The human brain therefore stores, associates, and can recall multiple data species with a single object. For example, the brain may associate xe2x80x9cbananaxe2x80x9d with the category of fruit, the spoken word banana, the image of a ripe yellow banana, the image of a non-ripe green banana, the smell of a banana, the texture of a banana peel, etc.
There is not currently a knowledge acquisition and retrieval apparatus or method that provides human-like storage, relationship, and retrieval for a multitude of data classes and species.
What is needed is an apparatus and method that simulates the human brain""s capacity to learn, relate, and recall relationships and associations for a multitude of different categories and data species.
The present invention provides an apparatus and method to organize, transform, and associate information between two conceptually graduated memory stages. For the acquisition stage, the invention provides an input system allowing presentation of multiple format data to the memory. As data is acquired, the memory stages build and maintain reciprocal associations. Such reciprocal associations allow cooperative processing between the memory stages to form a hierarchical association between related elements. This hierarchical association is exploited during the data retrieval process. Data retrieval may occur using as many as seven different retrieval algorithms that emulate the human cognitive functions.
Other objects and advantages of the present invention will become more obvious hereinafter in the specification and drawings.
These objects are accomplished with the present invention by a knowledge acquisition and retrieval apparatus and method that emulate the human brain and comprise at least one first memory segment, and a distinct second memory segment, wherein elements of the at least one first memory segment are reciprocally associated to elements of the second memory segment, and vice-versa. The at least one first memory segment comprises categorized data from the physical world, known as representational data, while the second memory segment contains abstract or conceptual data, otherwise known as consciousness data. Physical data comprises auditory data, language data, visual data, motion data, and sensory data, and each element of the at least one first memory segment is identified as auditory data, language data, visual data, motion data, or sensory data. By reciprocally associating the physical (representational) and conceptual (consciousness) data, a hierarchical structure is created that allows information retrieval by traversing the reciprocal associations. Varying retrieval algorithms traverse the hierarchical structure differently to generate specified system outputs. Retrieval algorithms are implemented to represent human information retrieval functions commonly known as reduction, imaging, deduction, recognition, recall, categorization, and reasoning.